Research
My research focuses on problems arising in mathematical data science. I am particularly interested in designing and analyzing iterative algorithms for large-scale data and leveraging and developing tools in numerical linear algebra, signal processing, machine learning, and probability.
Below, I highlight some recent works and provide code, when available, associated with the manuscript.
A complete list of my publications can be found on Google Scholar.
Kaczmarz Algorithms
E. H. Bergou, S. Boucherouite, A. Dutta, X. Li, and A. Ma. “A Note on Randomized Kaczmarz Algorithm for Solving Doubly- Noisy Linear Systems” Submitted (2023).
[arxiv] [code]J. Haddock, A. Ma, E. Rebrova. “On Subsampled Quantile Randomized Kaczmarz.” To appear in the Allerton Conference on Communication, Control, and Computing (2023).
[proceedings][arxiv]J. Haddock and A. Ma. “Greed Works: An Improved Analysis of Sampling Kaczmarz-Motkzin”. SIAM Journal on Mathematics of Data Science 3.1 (2021): 342-368.
[journal] [arxiv]
Tensor Methods
R. Grotheer, S. Li, A. Ma, D. Needell, and J. Qin. "Iterative Singular Tube Hard Thresholding Algorithms for Tensor Completion.” arXiv:2304.04860. Submitted (2023).
[arxiv] [code]A. Ma, D. Stöger, and Y. Zhu. "Robust recovery of low-rank matrices and low-tubal-rank tensors from noisy sketches.” arXiv:2206.00803 Accepted. To Appear in SIAM Journal on Matrix Analysis. (2023).
[journal] [arxiv] [code]A. Ma and D. Molitor. "Randomized Kaczmarz for tensor linear systems." BIT Numerical Mathematics 62.1 (2022): 171-194.
[journal] [arxiv] [code]
Data Visualization
Y. Liao, H. Luo, A. Ma. “Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization.” arXiv:2306.00357. Submitted (2023).
[arxiv] [code]K. Dover, Z. Cang, A. Ma, Q. Nie, and R. Vershynin. “AVIDA: Alternating method for Visualizing and Integrating Data.” Journal of Computational Science (2023): 101998.
[journal] [arxiv] [code]